Áreas de endemismo na América do Sul com base na distribuição geográfica dos besouros rola-bostas (Coleoptera, Scarabaeidae, Scarabaeinae)

• Autor(a) principal: Silva, Jorge Luiz da
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFMT
• Texto Completo: http://ri.ufmt.br/handle/1/2491
• topic: Biogeografia; Esforço amostral; Polígonos de Thiessen; Região neotropical; NDM - VNDM; CNPQ::CIENCIAS BIOLOGICAS::ECOLOGIA; Biogeography; Sampling effort; Thiessen polygons; Neotropical region; NDM - VNDM

We evaluated the geographic congruence of the distribution of the species/subspecies of dung beetles (Coleoptera, Scarabaeidae, Scarabaeinae) to identify areas of endemism for this group on both continental (Chapter 1) and local (Chapter 2) scales. Among the issues addressed on the identification of areas of endemism, the variation in the grid size used in the analysis and particular features of the distribution data (such as sample bias) affect the identification of areas of endemism, sometimes in uncertain way. Furthermore, differences in the distributions ranges of the taxa used to identify these areas can introduce variations in the distribution patterns observed. Thus, the objectives of both chapters is to evaluate if the distribution patterns observed on the dung beetles support the identification of areas of endemism and how the number and limits of the areas of endemism vary in relation to the size of the grids used in the analysis. In addition, we tested the robustness of the information of the sampling bias to enhance the selection of areas of endemism, relying on the known distribution of the taxa (Chapter 1). We also evaluated if the usage of different data of occurrence (local and continental) creates significant variations in the patterns of endemism observed (Chapter 2). The analysis of endemicity was performed with the program NDM/VNDM (eNDeMism and the Viewer of eNDeMism). The distribution data of dung beetles allowed us to detect areas of endemism, being most of them geographically consistent with distribution patterns already proposed in literature. Additionally, according to the size of the geographical units (grids), our results showed differences in the number and boundaries of these areas. The definition of endemic components based on sample bias allowed us the selection of regions with stronger information about the distribution of taxa. Regarding the usage of local or continental data of distribution, no evidences of conflicting patterns of endemism have been found. It demonstrates that even species widely distributed can be used to infer local pattern of endemism.